10,323 research outputs found
Binary Classifier Calibration using an Ensemble of Near Isotonic Regression Models
Learning accurate probabilistic models from data is crucial in many practical
tasks in data mining. In this paper we present a new non-parametric calibration
method called \textit{ensemble of near isotonic regression} (ENIR). The method
can be considered as an extension of BBQ, a recently proposed calibration
method, as well as the commonly used calibration method based on isotonic
regression. ENIR is designed to address the key limitation of isotonic
regression which is the monotonicity assumption of the predictions. Similar to
BBQ, the method post-processes the output of a binary classifier to obtain
calibrated probabilities. Thus it can be combined with many existing
classification models. We demonstrate the performance of ENIR on synthetic and
real datasets for the commonly used binary classification models. Experimental
results show that the method outperforms several common binary classifier
calibration methods. In particular on the real data, ENIR commonly performs
statistically significantly better than the other methods, and never worse. It
is able to improve the calibration power of classifiers, while retaining their
discrimination power. The method is also computationally tractable for large
scale datasets, as it is time, where is the number of
samples
Detection of radioactive material entering national ports: A Bayesian approach to radiation portal data
Given the potential for illicit nuclear material being used for terrorism,
most ports now inspect a large number of goods entering national borders for
radioactive cargo. The U.S. Department of Homeland Security is moving toward
one hundred percent inspection of all containers entering the U.S. at various
ports of entry for nuclear material. We propose a Bayesian classification
approach for the real-time data collected by the inline Polyvinyl Toluene
radiation portal monitors. We study the computational and asymptotic properties
of the proposed method and demonstrate its efficacy in simulations. Given data
available to the authorities, it should be feasible to implement this approach
in practice.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS334 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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